1. The Field of the Invention
The present invention relates to image processing. More specifically, the present invention relates to detection and isolation of surface features in an image.
2. Related Technology
Image processing includes the application of processing techniques to the domain of images. Some concepts for processing an image are more often used in the realm of one dimensional image analysis, while other concepts for processing images may be more applicable in the realm of two or three dimensional image analysis. Traditional image processing can implement concepts such as image resolution, dynamic range, bandwidth, filtering, connectivity, rotational invariance, differential operators, edge detection, and domain modulation.
As processors become faster, analog image processing techniques are increasingly being replaced by digital image processing techniques. Digital image processing techniques are characterized by versatility, reliability, accuracy, and ease of implementation. Digital imagery can be stored in various formats as geospatial data. Typically, a captured digital image begins as a raster image. A raster image is a data file or structure representing a generally rectangular grid of pixels, or points of color or intensity, on a computer monitor, paper, or other display device. Each pixel of the image is characterized by an attribute, such as color. The color, for example, of each pixel can be individually defined. Images in the RGB color space, for instance, often consist of colored pixels defined by three bytes, one byte each for red, green and blue. Less colorful images require less information per pixel. An image with only black and white pixels requires only a single bit for each pixel.
Another type of digital geospatial data is vector data. Vector data, or geometric modeling, is the use of geometrical primitives such as points, lines, curves, and polygons to represent objects. Vector data specifies a visual representation of the data with minimal information, and as a result files consisting of vector representations are much smaller than files consisting of raster data. Also, because the parameters of vector objects are stored and can be later modified by operations such as moving, scaling, rotating and filling, the operations do not degrade the quality of a drawing as compared to raster graphics.
One area where digital image processing techniques have become of increased importance is in the area of automated feature extraction, which may include algorithms that use cues to detect and isolate various areas of the geospatial data. These algorithms may be used to extract features from the geospatial data, such as roads, railways, and water bodies, for example, that can be displayed on maps or in a Geographic Information System (GIS). A GIS user, a cartographer, or other person can then view the results displayed in the map or a rendered view of the GIS. Currently, however, only single levels of feature extraction are conducted, and although several methods and concepts exist for extraction of features from geospatial data, there is still a need for improved automated feature extraction.